{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "sequence_map = {\n",
    "    'MOT17' : ['MOT17-13-FRCNN', 'MOT17-09-FRCNN', 'MOT17-10-FRCNN',\n",
    "       'MOT17-11-FRCNN', 'MOT17-04-FRCNN', 'MOT17-05-FRCNN',\n",
    "       'MOT17-02-FRCNN'],\n",
    "    'MOT20' : ['MOT20-01', 'MOT20-03', 'MOT20-02', 'MOT20-05']  \n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>video</th>\n",
       "      <th>frame_number</th>\n",
       "      <th>track_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>1541616</th>\n",
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       "      <td>1211</td>\n",
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       "    <tr>\n",
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       "      <td>1211</td>\n",
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       "    <tr>\n",
       "      <th>1541619</th>\n",
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       "      <td>1447</td>\n",
       "      <td>1211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1541620</th>\n",
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       "      <td>1448</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>1541621 rows × 4 columns</p>\n",
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      ],
      "text/plain": [
       "        dataset           video  frame_number  track_id\n",
       "0         MOT17  MOT17-13-FRCNN             1         1\n",
       "1         MOT17  MOT17-13-FRCNN             2         1\n",
       "2         MOT17  MOT17-13-FRCNN             3         1\n",
       "3         MOT17  MOT17-13-FRCNN             4         1\n",
       "4         MOT17  MOT17-13-FRCNN             5         1\n",
       "...         ...             ...           ...       ...\n",
       "1541616   MOT20        MOT20-05          1444      1211\n",
       "1541617   MOT20        MOT20-05          1445      1211\n",
       "1541618   MOT20        MOT20-05          1446      1211\n",
       "1541619   MOT20        MOT20-05          1447      1211\n",
       "1541620   MOT20        MOT20-05          1448      1211\n",
       "\n",
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      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_track_id_per_frame(dataset):\n",
    "    sequences = sequence_map[dataset]\n",
    "    final_data = []\n",
    "\n",
    "    for seq in sequences:\n",
    "        \n",
    "        relative_path = f'datasets/{dataset}/train/{seq}/gt/gt.txt'\n",
    "        absolute_path = os.path.join(os.path.dirname(os.getcwd()), relative_path)\n",
    "\n",
    "        # Read the ground truth file\n",
    "        gt = pd.read_csv(absolute_path, header=None)\n",
    "        for line in gt.values:\n",
    "            frame_number, track_id = line[0], line[1]\n",
    "            final_data.append({\n",
    "                'dataset': dataset,\n",
    "                'video': seq,\n",
    "                'frame_number': int(frame_number),\n",
    "                'track_id': int(track_id)\n",
    "            })\n",
    "\n",
    "    return pd.DataFrame(final_data)\n",
    "\n",
    "mot17_gt = get_track_id_per_frame('MOT17')\n",
    "mot20_gt = get_track_id_per_frame('MOT20')\n",
    "\n",
    "mot_gt = pd.concat([mot17_gt, mot20_gt], ignore_index=True)\n",
    "mot_gt"
   ]
  },
  {
   "cell_type": "code",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>video</th>\n",
       "      <th>frame_number</th>\n",
       "      <th>track_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MOT17</td>\n",
       "      <td>MOT17-02-FRCNN</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MOT17</td>\n",
       "      <td>MOT17-02-FRCNN</td>\n",
       "      <td>2</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MOT17</td>\n",
       "      <td>MOT17-02-FRCNN</td>\n",
       "      <td>3</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MOT17</td>\n",
       "      <td>MOT17-02-FRCNN</td>\n",
       "      <td>4</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MOT17</td>\n",
       "      <td>MOT17-02-FRCNN</td>\n",
       "      <td>5</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14242</th>\n",
       "      <td>MOT20</td>\n",
       "      <td>MOT20-05</td>\n",
       "      <td>3311</td>\n",
       "      <td>225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14243</th>\n",
       "      <td>MOT20</td>\n",
       "      <td>MOT20-05</td>\n",
       "      <td>3312</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14244</th>\n",
       "      <td>MOT20</td>\n",
       "      <td>MOT20-05</td>\n",
       "      <td>3313</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14245</th>\n",
       "      <td>MOT20</td>\n",
       "      <td>MOT20-05</td>\n",
       "      <td>3314</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14246</th>\n",
       "      <td>MOT20</td>\n",
       "      <td>MOT20-05</td>\n",
       "      <td>3315</td>\n",
       "      <td>227</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14247 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      dataset           video  frame_number  track_id\n",
       "0       MOT17  MOT17-02-FRCNN             1        39\n",
       "1       MOT17  MOT17-02-FRCNN             2        39\n",
       "2       MOT17  MOT17-02-FRCNN             3        39\n",
       "3       MOT17  MOT17-02-FRCNN             4        39\n",
       "4       MOT17  MOT17-02-FRCNN             5        39\n",
       "...       ...             ...           ...       ...\n",
       "14242   MOT20        MOT20-05          3311       225\n",
       "14243   MOT20        MOT20-05          3312       226\n",
       "14244   MOT20        MOT20-05          3313       226\n",
       "14245   MOT20        MOT20-05          3314       226\n",
       "14246   MOT20        MOT20-05          3315       227\n",
       "\n",
       "[14247 rows x 4 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tracker_count_per_frame = mot_gt.groupby(['dataset', 'video', 'frame_number']).agg({'track_id': 'count'}).reset_index()\n",
    "tracker_count_per_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Define color palette\n",
    "colors = {\"MOT17\": \"blue\", \"MOT20\": \"red\"}\n",
    "\n",
    "plt.figure(figsize=(8, 5))\n",
    "\n",
    "# Plot distribution for both datasets\n",
    "for dataset in [\"MOT17\", \"MOT20\"]:\n",
    "    subset = tracker_count_per_frame[tracker_count_per_frame[\"dataset\"] == dataset]\n",
    "    \n",
    "    sns.histplot(\n",
    "        data=subset,\n",
    "        x=\"track_id\",\n",
    "        stat=\"count\",  # Show actual counts instead of probability density\n",
    "        bins=30,\n",
    "        color=colors[dataset],\n",
    "        label=dataset,\n",
    "        alpha=0.6  # Transparency for overlap visualization\n",
    "    )\n",
    "\n",
    "# Labels and legend\n",
    "plt.title(\"Distribution of Track IDs Per Frame\", fontsize=18)\n",
    "plt.xlabel(\"Number of Track IDs per Frame\", fontsize=18)\n",
    "plt.ylabel(\"Density\", fontsize=18)  # Changed from Probability Density\n",
    "plt.xticks(fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.legend(title=\"Dataset\", fontsize=15, title_fontsize=15)\n",
    "\n",
    "plt.grid(False)\n",
    "plt.tight_layout()\n",
    "plt.savefig('pdf_dataset.png')  # Updated filename to reflect distribution\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tracker_count_per_frame[\"max_frame\"] = tracker_count_per_frame.groupby(\"video\")[\"frame_number\"].transform(\"max\")\n",
    "second_half_df = tracker_count_per_frame[tracker_count_per_frame[\"frame_number\"] > tracker_count_per_frame[\"max_frame\"] / 2]\n",
    "\n",
    "plt.figure(figsize=(8, 5))\n",
    "\n",
    "# Plot CDFs for both datasets\n",
    "for dataset in [\"MOT17\", \"MOT20\"]:\n",
    "    subset = second_half_df[second_half_df[\"dataset\"] == dataset]\n",
    "    \n",
    "    sns.ecdfplot(\n",
    "        data=subset,\n",
    "        x=\"track_id\",\n",
    "        color=colors[dataset],\n",
    "        label=dataset,\n",
    "        linewidth=4  # Make lines more prominent\n",
    "    )\n",
    "\n",
    "# Labels and legend\n",
    "plt.title(\"CDF of Track IDs Per Frame (Second Half)\", fontsize=18)\n",
    "plt.xlabel(\"Number of Track IDs per Frame\", fontsize=18)\n",
    "plt.ylabel(\"Cumulative Probability\", fontsize=18)\n",
    "plt.xticks(fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.legend(title=\"Dataset\", fontsize=15, title_fontsize=15)\n",
    "\n",
    "plt.grid(False)  # Disable grid for a clean look\n",
    "plt.tight_layout()\n",
    "plt.savefig('cdf.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
